"""
Calculating grid gradient with custom ``azimuth`` and ``normalize`` parameters
==============================================================================

The :func:`pygmt.grdgradient` function calculates the gradient of a grid file.
As input, :func:`pygmt.grdgradient` gets an :class:`xarray.DataArray` object
or a path string to a grid file. It then calculates the respective gradient
and returns an :class:`xarray.DataArray` object. The example below sets two
main parameters:

- ``azimuth`` to set the illumination light source direction (0° is North,
  90° is East, 180° is South, 270° is West).
- ``normalize`` to enhance the three-dimensional sense of the topography.

The ``normalize`` parameter calculates the azimuthal gradient of each point
along a certain azimuth angle, then adjusts the brightness value of the color
according to the positive/negative of the azimuthal gradient and the amplitude
of each point.
"""

# %%
import pygmt

# Load the 3 arc-minutes global relief grid in the target area around Caucasus
grid = pygmt.datasets.load_earth_relief(resolution="03m", region=[35, 50, 35, 45])

fig = pygmt.Figure()

# Define a colormap to be used for topography
pygmt.makecpt(cmap="terra", series=[-7000, 7000])

# Define figure configuration
pygmt.config(FONT_TITLE="10p,5", MAP_TITLE_OFFSET="1p", MAP_FRAME_TYPE="plain")

# Setup subplot panels with three rows and four columns
with fig.subplot(
    nrows=3,
    ncols=4,
    figsize=("28c", "21c"),
    sharex="b",
    sharey="l",
):
    # E.g. "0/90" illuminates light source from the North (top) and East
    # (right), and so on
    for azi in ["0/90", "0/300", "180/225"]:
        # "e" and "t" are cumulative Laplace distribution and cumulative
        # Cauchy distribution, respectively
        # "amp" (e.g. 1 or 10) controls the brightness value of the color
        for nor in ["t1", "e1", "t10", "e10"]:
            # Making an intensity DataArray using azimuth and normalize
            # parameters
            shade = pygmt.grdgradient(grid=grid, azimuth=azi, normalize=nor)
            fig.grdimage(
                grid=grid,
                shading=shade,
                projection="M?",
                frame=["a4f2", f"+tazimuth={azi}, normalize={nor}"],
                cmap=True,
                panel=True,
            )

fig.colorbar(position="JBC+w10c/0.25c+h", frame="xa2000f500+lElevation (m)")

fig.show()